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   <div id="projectname">OpenCV
   &#160;<span id="projectnumber">4.5.2</span>
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   <div id="projectbrief">Open Source Computer Vision</div>
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<li class="navelem"><a class="el" href="../../d9/df8/tutorial_root.html">OpenCV Tutorials</a></li><li class="navelem"><a class="el" href="../../d9/d97/tutorial_table_of_content_features2d.html">2D Features framework (feature2d module)</a></li>  </ul>
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<div class="title">Feature Description </div>  </div>
</div><!--header-->
<div class="contents">
<div class="textblock"><p><b>Prev Tutorial:</b> <a class="el" href="../../d7/d66/tutorial_feature_detection.html">Feature Detection</a></p>
<p><b>Next Tutorial:</b> <a class="el" href="../../d5/d6f/tutorial_feature_flann_matcher.html">Feature Matching with FLANN</a></p>
<table class="doxtable">
<tr>
<th align="right"></th><th align="left"></th></tr>
<tr>
<td align="right">Original author </td><td align="left">Ana Huamán </td></tr>
<tr>
<td align="right">Compatibility </td><td align="left">OpenCV &gt;= 3.0 </td></tr>
</table>
<h2>Goal </h2>
<p>In this tutorial you will learn how to:</p>
<ul>
<li>Use the <a class="el" href="../../da/d9b/group__features2d.html#gadd5cf7c76865f14468cfdd9cc08eb990">cv::DescriptorExtractor</a> interface in order to find the feature vector correspondent to the keypoints. Specifically:<ul>
<li>Use <a class="el" href="../../d5/df7/classcv_1_1xfeatures2d_1_1SURF.html" title="Class for extracting Speeded Up Robust Features from an image  . ">cv::xfeatures2d::SURF</a> and its function <a class="el" href="../../d0/d13/classcv_1_1Feature2D.html#ab3cce8d56f4fc5e1d530b5931e1e8dc0" title="Computes the descriptors for a set of keypoints detected in an image (first variant) or image set (se...">cv::xfeatures2d::SURF::compute</a> to perform the required calculations.</li>
<li>Use a <a class="el" href="../../db/d39/classcv_1_1DescriptorMatcher.html">cv::DescriptorMatcher</a> to match the features vector</li>
<li>Use the function <a class="el" href="../../d4/d5d/group__features2d__draw.html#gad8f463ccaf0dc6f61083abd8717c261a">cv::drawMatches</a> to draw the detected matches.</li>
</ul>
</li>
</ul>
<dl class="section warning"><dt>Warning</dt><dd>You need the <a href="https://github.com/opencv/opencv_contrib">OpenCV contrib modules</a> to be able to use the SURF features (alternatives are ORB, KAZE, ... features).</dd></dl>
<h2>Theory </h2>
<h2>Code </h2>
 <div class='newInnerHTML' title='cpp' style='display: none;'>C++</div><div class='toggleable_div label_cpp' style='display: none;'><p> This tutorial code's is shown lines below. You can also download it from <a href="https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/features2D/feature_description/SURF_matching_Demo.cpp">here</a> </p><div class="fragment"><div class="line"><span class="preprocessor">#include &lt;iostream&gt;</span></div><div class="line"><span class="preprocessor">#include &quot;<a class="code" href="../../d0/d9c/core_2include_2opencv2_2core_8hpp.html">opencv2/core.hpp</a>&quot;</span></div><div class="line"><span class="preprocessor">#ifdef HAVE_OPENCV_XFEATURES2D</span></div><div class="line"><span class="preprocessor">#include &quot;<a class="code" href="../../d4/dd5/highgui_8hpp.html">opencv2/highgui.hpp</a>&quot;</span></div><div class="line"><span class="preprocessor">#include &quot;<a class="code" href="../../d5/d0d/features2d_8hpp.html">opencv2/features2d.hpp</a>&quot;</span></div><div class="line"><span class="preprocessor">#include &quot;<a class="code" href="../../dc/daa/xfeatures2d_8hpp.html">opencv2/xfeatures2d.hpp</a>&quot;</span></div><div class="line"></div><div class="line"><span class="keyword">using namespace </span><a class="code" href="../../d2/d75/namespacecv.html">cv</a>;</div><div class="line"><span class="keyword">using namespace </span><a class="code" href="../../d3/df6/namespacecv_1_1xfeatures2d.html">cv::xfeatures2d</a>;</div><div class="line"><span class="keyword">using</span> std::cout;</div><div class="line"><span class="keyword">using</span> std::endl;</div><div class="line"></div><div class="line"><span class="keyword">const</span> <span class="keywordtype">char</span>* keys =</div><div class="line">    <span class="stringliteral">&quot;{ help h |                  | Print help message. }&quot;</span></div><div class="line">    <span class="stringliteral">&quot;{ input1 | box.png          | Path to input image 1. }&quot;</span></div><div class="line">    <span class="stringliteral">&quot;{ input2 | box_in_scene.png | Path to input image 2. }&quot;</span>;</div><div class="line"></div><div class="line"><span class="keywordtype">int</span> main( <span class="keywordtype">int</span> argc, <span class="keywordtype">char</span>* argv[] )</div><div class="line">{</div><div class="line">    <a class="code" href="../../d0/d2e/classcv_1_1CommandLineParser.html">CommandLineParser</a> parser( argc, argv, keys );</div><div class="line">    <a class="code" href="../../d3/d63/classcv_1_1Mat.html">Mat</a> img1 = <a class="code" href="../../d4/da8/group__imgcodecs.html#ga288b8b3da0892bd651fce07b3bbd3a56">imread</a>( <a class="code" href="../../d6/dba/group__core__utils__samples.html#ga3a33b00033b46c698ff6340d95569c13">samples::findFile</a>( parser.get&lt;<a class="code" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>&gt;(<span class="stringliteral">&quot;input1&quot;</span>) ), <a class="code" href="../../d8/d6a/group__imgcodecs__flags.html#gga61d9b0126a3e57d9277ac48327799c80ae29981cfc153d3b0cef5c0daeedd2125">IMREAD_GRAYSCALE</a> );</div><div class="line">    <a class="code" href="../../d3/d63/classcv_1_1Mat.html">Mat</a> img2 = <a class="code" href="../../d4/da8/group__imgcodecs.html#ga288b8b3da0892bd651fce07b3bbd3a56">imread</a>( <a class="code" href="../../d6/dba/group__core__utils__samples.html#ga3a33b00033b46c698ff6340d95569c13">samples::findFile</a>( parser.get&lt;<a class="code" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>&gt;(<span class="stringliteral">&quot;input2&quot;</span>) ), <a class="code" href="../../d8/d6a/group__imgcodecs__flags.html#gga61d9b0126a3e57d9277ac48327799c80ae29981cfc153d3b0cef5c0daeedd2125">IMREAD_GRAYSCALE</a> );</div><div class="line">    <span class="keywordflow">if</span> ( img1.<a class="code" href="../../d3/d63/classcv_1_1Mat.html#abbec3525a852e77998aba034813fded4">empty</a>() || img2.<a class="code" href="../../d3/d63/classcv_1_1Mat.html#abbec3525a852e77998aba034813fded4">empty</a>() )</div><div class="line">    {</div><div class="line">        cout &lt;&lt; <span class="stringliteral">&quot;Could not open or find the image!\n&quot;</span> &lt;&lt; endl;</div><div class="line">        parser.printMessage();</div><div class="line">        <span class="keywordflow">return</span> -1;</div><div class="line">    }</div><div class="line"></div><div class="line">    <span class="comment">//-- Step 1: Detect the keypoints using SURF Detector, compute the descriptors</span></div><div class="line">    <span class="keywordtype">int</span> minHessian = 400;</div><div class="line">    <a class="code" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr&lt;SURF&gt;</a> detector = <a class="code" href="../../d5/df7/classcv_1_1xfeatures2d_1_1SURF.html#a436553ca44d9a2238761ddbee5b395e5">SURF::create</a>( minHessian );</div><div class="line">    std::vector&lt;KeyPoint&gt; keypoints1, keypoints2;</div><div class="line">    <a class="code" href="../../d3/d63/classcv_1_1Mat.html">Mat</a> descriptors1, descriptors2;</div><div class="line">    detector-&gt;detectAndCompute( img1, <a class="code" href="../../dc/d84/group__core__basic.html#gad9287b23bba2fed753b36ef561ae7346">noArray</a>(), keypoints1, descriptors1 );</div><div class="line">    detector-&gt;detectAndCompute( img2, <a class="code" href="../../dc/d84/group__core__basic.html#gad9287b23bba2fed753b36ef561ae7346">noArray</a>(), keypoints2, descriptors2 );</div><div class="line"></div><div class="line">    <span class="comment">//-- Step 2: Matching descriptor vectors with a brute force matcher</span></div><div class="line">    <span class="comment">// Since SURF is a floating-point descriptor NORM_L2 is used</span></div><div class="line">    <a class="code" href="../../dc/d84/group__core__basic.html#ga6395ca871a678020c4a31fadf7e8cc63">Ptr&lt;DescriptorMatcher&gt;</a> matcher = <a class="code" href="../../db/d39/classcv_1_1DescriptorMatcher.html#ab5dc5036569ecc8d47565007fa518257">DescriptorMatcher::create</a>(<a class="code" href="../../db/d39/classcv_1_1DescriptorMatcher.html#af8b6f4acb8f1a9ea6b73bfcb86b80c3baddf99aae344c73b63d77764440711b76">DescriptorMatcher::BRUTEFORCE</a>);</div><div class="line">    std::vector&lt; DMatch &gt; matches;</div><div class="line">    matcher-&gt;match( descriptors1, descriptors2, matches );</div><div class="line"></div><div class="line">    <span class="comment">//-- Draw matches</span></div><div class="line">    <a class="code" href="../../d3/d63/classcv_1_1Mat.html">Mat</a> img_matches;</div><div class="line">    <a class="code" href="../../d4/d5d/group__features2d__draw.html#gad8f463ccaf0dc6f61083abd8717c261a">drawMatches</a>( img1, keypoints1, img2, keypoints2, matches, img_matches );</div><div class="line"></div><div class="line">    <span class="comment">//-- Show detected matches</span></div><div class="line">    <a class="code" href="../../d7/dfc/group__highgui.html#ga453d42fe4cb60e5723281a89973ee563">imshow</a>(<span class="stringliteral">&quot;Matches&quot;</span>, img_matches );</div><div class="line"></div><div class="line">    <a class="code" href="../../d7/dfc/group__highgui.html#ga5628525ad33f52eab17feebcfba38bd7">waitKey</a>();</div><div class="line">    <span class="keywordflow">return</span> 0;</div><div class="line">}</div><div class="line"><span class="preprocessor">#else</span></div><div class="line"><span class="keywordtype">int</span> main()</div><div class="line">{</div><div class="line">    std::cout &lt;&lt; <span class="stringliteral">&quot;This tutorial code needs the xfeatures2d contrib module to be run.&quot;</span> &lt;&lt; std::endl;</div><div class="line">    <span class="keywordflow">return</span> 0;</div><div class="line">}</div><div class="line"><span class="preprocessor">#endif</span></div></div><!-- fragment -->  </div>  <div class='newInnerHTML' title='java' style='display: none;'>Java</div><div class='toggleable_div label_java' style='display: none;'><p> This tutorial code's is shown lines below. You can also download it from <a href="https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/features2D/feature_description/SURFMatchingDemo.java">here</a> </p><div class="fragment"><div class="line"><span class="keyword">import</span> org.opencv.core.Core;</div><div class="line"><span class="keyword">import</span> org.opencv.core.Mat;</div><div class="line"><span class="keyword">import</span> org.opencv.core.MatOfDMatch;</div><div class="line"><span class="keyword">import</span> org.opencv.core.MatOfKeyPoint;</div><div class="line"><span class="keyword">import</span> org.opencv.features2d.DescriptorMatcher;</div><div class="line"><span class="keyword">import</span> org.opencv.features2d.Features2d;</div><div class="line"><span class="keyword">import</span> org.opencv.highgui.HighGui;</div><div class="line"><span class="keyword">import</span> org.opencv.imgcodecs.Imgcodecs;</div><div class="line"><span class="keyword">import</span> org.opencv.xfeatures2d.SURF;</div><div class="line"></div><div class="line"><span class="keyword">class </span>SURFMatching {</div><div class="line">    <span class="keyword">public</span> <span class="keywordtype">void</span> run(<a class="code" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>[] args) {</div><div class="line">        <a class="code" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> filename1 = args.length &gt; 1 ? args[0] : <span class="stringliteral">&quot;../data/box.png&quot;</span>;</div><div class="line">        <a class="code" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> filename2 = args.length &gt; 1 ? args[1] : <span class="stringliteral">&quot;../data/box_in_scene.png&quot;</span>;</div><div class="line">        Mat img1 = Imgcodecs.imread(filename1, Imgcodecs.IMREAD_GRAYSCALE);</div><div class="line">        Mat img2 = Imgcodecs.imread(filename2, Imgcodecs.IMREAD_GRAYSCALE);</div><div class="line">        <span class="keywordflow">if</span> (img1.empty() || img2.empty()) {</div><div class="line">            System.err.println(<span class="stringliteral">&quot;Cannot read images!&quot;</span>);</div><div class="line">            System.exit(0);</div><div class="line">        }</div><div class="line"></div><div class="line">        <span class="comment">//-- Step 1: Detect the keypoints using SURF Detector, compute the descriptors</span></div><div class="line">        <span class="keywordtype">double</span> hessianThreshold = 400;</div><div class="line">        <span class="keywordtype">int</span> nOctaves = 4, nOctaveLayers = 3;</div><div class="line">        <span class="keywordtype">boolean</span> extended = <span class="keyword">false</span>, upright = <span class="keyword">false</span>;</div><div class="line">        SURF detector = SURF.<a class="code" href="../../d3/d63/classcv_1_1Mat.html#a55ced2c8d844d683ea9a725c60037ad0">create</a>(hessianThreshold, nOctaves, nOctaveLayers, extended, upright);</div><div class="line">        MatOfKeyPoint keypoints1 = <span class="keyword">new</span> MatOfKeyPoint(), keypoints2 = <span class="keyword">new</span> MatOfKeyPoint();</div><div class="line">        Mat descriptors1 = <span class="keyword">new</span> Mat(), descriptors2 = <span class="keyword">new</span> Mat();</div><div class="line">        detector.detectAndCompute(img1, <span class="keyword">new</span> Mat(), keypoints1, descriptors1);</div><div class="line">        detector.detectAndCompute(img2, <span class="keyword">new</span> Mat(), keypoints2, descriptors2);</div><div class="line"></div><div class="line">        <span class="comment">//-- Step 2: Matching descriptor vectors with a brute force matcher</span></div><div class="line">        <span class="comment">// Since SURF is a floating-point descriptor NORM_L2 is used</span></div><div class="line">        DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE);</div><div class="line">        MatOfDMatch matches = <span class="keyword">new</span> MatOfDMatch();</div><div class="line">        matcher.match(descriptors1, descriptors2, matches);</div><div class="line"></div><div class="line">        <span class="comment">//-- Draw matches</span></div><div class="line">        Mat imgMatches = <span class="keyword">new</span> Mat();</div><div class="line">        Features2d.drawMatches(img1, keypoints1, img2, keypoints2, matches, imgMatches);</div><div class="line"></div><div class="line">        HighGui.imshow(<span class="stringliteral">&quot;Matches&quot;</span>, imgMatches);</div><div class="line">        HighGui.waitKey(0);</div><div class="line"></div><div class="line">        System.exit(0);</div><div class="line">    }</div><div class="line">}</div><div class="line"></div><div class="line"><span class="keyword">public</span> <span class="keyword">class </span>SURFMatchingDemo {</div><div class="line">    <span class="keyword">public</span> <span class="keyword">static</span> <span class="keywordtype">void</span> main(<a class="code" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>[] args) {</div><div class="line">        <span class="comment">// Load the native OpenCV library</span></div><div class="line">        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);</div><div class="line"></div><div class="line">        <span class="keyword">new</span> SURFMatching().run(args);</div><div class="line">    }</div><div class="line">}</div></div><!-- fragment -->  </div>  <div class='newInnerHTML' title='python' style='display: none;'>Python</div><div class='toggleable_div label_python' style='display: none;'><p> This tutorial code's is shown lines below. You can also download it from <a href="https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/features2D/feature_description/SURF_matching_Demo.py">here</a> </p><div class="fragment"><div class="line"><span class="keyword">from</span> __future__ <span class="keyword">import</span> print_function</div><div class="line"><span class="keyword">import</span> cv2 <span class="keyword">as</span> cv</div><div class="line"><span class="keyword">import</span> numpy <span class="keyword">as</span> np</div><div class="line"><span class="keyword">import</span> argparse</div><div class="line"></div><div class="line">parser = argparse.ArgumentParser(description=<span class="stringliteral">&#39;Code for Feature Detection tutorial.&#39;</span>)</div><div class="line">parser.add_argument(<span class="stringliteral">&#39;--input1&#39;</span>, help=<span class="stringliteral">&#39;Path to input image 1.&#39;</span>, default=<span class="stringliteral">&#39;box.png&#39;</span>)</div><div class="line">parser.add_argument(<span class="stringliteral">&#39;--input2&#39;</span>, help=<span class="stringliteral">&#39;Path to input image 2.&#39;</span>, default=<span class="stringliteral">&#39;box_in_scene.png&#39;</span>)</div><div class="line">args = parser.parse_args()</div><div class="line"></div><div class="line">img1 = <a class="code" href="../../d4/da8/group__imgcodecs.html#ga288b8b3da0892bd651fce07b3bbd3a56">cv.imread</a>(<a class="code" href="../../d6/dba/group__core__utils__samples.html#ga3a33b00033b46c698ff6340d95569c13">cv.samples.findFile</a>(args.input1), cv.IMREAD_GRAYSCALE)</div><div class="line">img2 = <a class="code" href="../../d4/da8/group__imgcodecs.html#ga288b8b3da0892bd651fce07b3bbd3a56">cv.imread</a>(<a class="code" href="../../d6/dba/group__core__utils__samples.html#ga3a33b00033b46c698ff6340d95569c13">cv.samples.findFile</a>(args.input2), cv.IMREAD_GRAYSCALE)</div><div class="line"><span class="keywordflow">if</span> img1 <span class="keywordflow">is</span> <span class="keywordtype">None</span> <span class="keywordflow">or</span> img2 <span class="keywordflow">is</span> <span class="keywordtype">None</span>:</div><div class="line">    <a class="code" href="../../df/d57/namespacecv_1_1dnn.html#a701210a0203f2786cbfd04b2bd56da47">print</a>(<span class="stringliteral">&#39;Could not open or find the images!&#39;</span>)</div><div class="line">    exit(0)</div><div class="line"></div><div class="line"><span class="comment">#-- Step 1: Detect the keypoints using SURF Detector, compute the descriptors</span></div><div class="line">minHessian = 400</div><div class="line">detector = cv.xfeatures2d_SURF.create(hessianThreshold=minHessian)</div><div class="line">keypoints1, descriptors1 = detector.detectAndCompute(img1, <span class="keywordtype">None</span>)</div><div class="line">keypoints2, descriptors2 = detector.detectAndCompute(img2, <span class="keywordtype">None</span>)</div><div class="line"></div><div class="line"><span class="comment">#-- Step 2: Matching descriptor vectors with a brute force matcher</span></div><div class="line"><span class="comment"># Since SURF is a floating-point descriptor NORM_L2 is used</span></div><div class="line">matcher = cv.DescriptorMatcher_create(cv.DescriptorMatcher_BRUTEFORCE)</div><div class="line">matches = matcher.match(descriptors1, descriptors2)</div><div class="line"></div><div class="line"><span class="comment">#-- Draw matches</span></div><div class="line">img_matches = np.empty((<a class="code" href="../../d1/d10/classcv_1_1MatExpr.html#a6dff8b6e9105b6d817b493e7be157c90">max</a>(img1.shape[0], img2.shape[0]), img1.shape[1]+img2.shape[1], 3), dtype=np.uint8)</div><div class="line"><a class="code" href="../../d4/d5d/group__features2d__draw.html#ga62fbedb5206ab2faf411797e7055c90f">cv.drawMatches</a>(img1, keypoints1, img2, keypoints2, matches, img_matches)</div><div class="line"></div><div class="line"><span class="comment">#-- Show detected matches</span></div><div class="line"><a class="code" href="../../df/d24/group__highgui__opengl.html#gaae7e90aa3415c68dba22a5ff2cefc25d">cv.imshow</a>(<span class="stringliteral">&#39;Matches&#39;</span>, img_matches)</div><div class="line"></div><div class="line"><a class="code" href="../../d7/dfc/group__highgui.html#ga5628525ad33f52eab17feebcfba38bd7">cv.waitKey</a>()</div></div><!-- fragment -->  </div> <h2>Explanation </h2>
<h2>Result </h2>
<p>Here is the result after applying the BruteForce matcher between the two original images:</p>
<div class="image">
<img src="../../Feature_Description_BruteForce_Result.jpg" alt="Feature_Description_BruteForce_Result.jpg"/>
</div>
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